Current Computer - Aided Drug Design - Volume 3, Issue 2, 2007

The drug discovery research for new potent anti-viral drugs is one of the most interesting areas that may adopt a long process ranging from screening to marketing. Several attempts have been made in this direction because of the viral infection such as HIV, dengue and particular emerging diseases such as SARS and avian influenza. However, the severe problems are faced due to the mutation of DNA as well as RNA of the virus. For this reason, computer-aided drug design and virtual screening at the early stages of drug development are urgently needed. Specific to this Hot Topic issue is the strong belief that knowledge and different disciplines of anti-viral drug researches can support to each other. The progress in one area is not known to scientists dealing with the same problem but belong to another discipline. For example, similar approaches of computer-aided drug design for two different anti-viral targets/enzymes have been applied to search for bioactive compounds as pharmaceutical drugs, with little mutual benefit. Thus in this issue, a special effort has been made to gather contributions from different viral targets, and to bridge the gap between various computational approaches and the knowledge-based anti-viral community. The Hot Topic on Anti-viral agents and Emerging Diseases has been separated into two parts. In the first part, a mini-review by Beyer et al. focuses on a most important target for anti-AIDS therapy, HIV-1 Reverse Transcriptase (HIV-1 RT). Structural information as obtained by X-ray crystallographic studies on the enzyme and on enzyme complexes provide the protein-inhibitor interaction. By applying molecular simulations, the dynamic behavior of this biomolecular system can be obtained in order to get some insight into the molecular flexibilities and into the detailed inhibition mechanism. The paper emphasizes that the combination of various theoretical methods leads to faster and more accurate algorithms to perform QSAR studies and in silico screening. Weaknesses like the molecular alignment in 3D-QSAR or the ambiguities in docking procedures in virtual screening can be avoided by applying such combinatorial procedures. The mini-review by Rahman et al. is related to the issue of the protein of the dengue virus. Much work has been done on dengue virus, and on searching for vaccine and therapeutic agents for DF and DHF/DSS. However, till date, there is still no suitable vaccine or therapeutic agents available for either type of fever. The discovery of potential candidates for vaccines is the result of a number of researches for many years by employing various strategies. One major difficulty faced by researchers in their efforts to develop a vaccine for dengue is due to the existence of 4 different serotypes of dengue virus, which has to be addressed in order to develop a successful vaccine. The review includes some of the work and strategies that have been carried out in the quest for finding vaccines and therapeutic drugs for dengue, particularly those employing computer-aided approaches. To gain some knowledge for emerging diseases, such as avian influenza, a focus of the next mini-review by Sangma et al. is placed on avian influenza targeted on neuraminidase. Since there are only two approved drugs and the drug resistance strains seem to be severe, an urgent need is felt for the discovery of new anti-neuraminidase compounds. Current development of neuraminidase inhibitors is due to protein-based design. In this review, the basic concepts underlying the design of new drugs, and a number of drugs that are currently undergoing testing, are presented. Also various computational techniques that can be applied to enhance the drug activity and to extract basic knowledge, which we need to prepare ourselves for the pandemic, are discussed. The second part of this Hot Topic issue (Anti-viral agents and Emerging Diseases (part II)), starts with a quite comprehensive review by Briggs et al. which presents an overview on the efforts undertaken to identify selective HIV-1 Integrase (HIV-1 IN) inhibitors with the goal of improving the outcome of AIDS therapy using highly active anti retroviral therapy (HAART). As computational technology has grown rapidly and is increasingly being used worldwide to accelerate the drug discovery processes, besides its application to HIV-1 IN and its inhibitors.........

HIV-1 Reverse transcriptase (RT) is an essential enzyme for HIV-1 replication and, therefore, it is an important target for the attack of antiviral agents. Although some products are already on the market, there is need to design new drugs, because mutation in drug interacting disease proteins decreases the efficiency of the existing drugs. Non-nucleoside RT inhibitors fill up an allosteric, mainly hydrophobic pocket in a distinct distance from the enzyme's active center. X-ray crystallographic investigations on the enzyme and on enzyme complexes provide information about the structural consequences of the protein-inhibitor interaction. Applying molecular simulations the dynamic behaviour of these biomolecular systems can be obtained in order to get some insight into the molecular flexibilities and into the detailed inhibition mechanism. Amino acids which are important for the inhibition mechanism and the interaction with inhibitor molecules can be identified for further considerations with more accurate molecular calculations. QSAR studies allow the development of proper prediction models, which are used to design new drugs. Combination of molecular docking, energy minimization and MD or MC calculations with various QSAR methods will support screening methods to find new lead compounds.

Dengue is a serious emerging or re-emerging infectious disease that is endemic in over 100 countries. There has been an estimated of 50 million infection per year globally with more than 2.5 billion people are at risk for epidemic transmission. The major burden for dengue is in the south-east Asia and the western Pacific although there have been increasing reports of this disease in the Americas. This infectious disease is caused by the dengue virus which is a member of the Flaviviridae and is spread by the highly domesticated Aedes aegypti mosquito. There are two principal illnesses associated with dengue which are Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF). The former is a flu-like illness with symptoms like fever, headaches, joint aches and rashes while the latter is more severe and often fatal complication of DF as a result of the dengue shock syndrome (DSS). To date, there is no licensed vaccine or therapeutic drug available for DF and DHF/DSS, although there have been reports of some vaccine candidates in clinical trials. The treatment for DF and DHF/DSS has only been supportive thus far. This paper discusses the protein of the dengue virus as well as reviews some of the work and strategies that have been carried out in the quest for finding vaccines and therapeutic drugs for dengue, particularly those employing computer-aided approaches.

It will take only a few years, even with constant surveillance, before the avian influenza subtype H5N1 virus has spread around the world. The main agents that can use to fight the coming outbreak, while vaccines are not yet available and only useful in prevention, are anti-neuraminidase drugs. Only two approved drugs are available and supplies are inadequate for everyone. Even worse is the likelihood that drug resistance strains will be found, hence there is an urgent need for new antineuraminidase compounds. Current development of neuraminidase inhibitors is due to structure-based designed. This article presents the basic concepts underlying the design of new drugs, and a number of drugs that are currently undergoing testing. Also, various computational techniques that can be applied to enhance the drug activity and extract basic knowledge, whichis necessary for us to prepare for the pandemic, are also discussed.

In silico high throughput screens provide an efficient (time and money) and effective (with comparable or better accuracy) alternatives in comparison to their experimental counterparts, and hence is of enormous interest to drug discovery research. However the assessment of a variety of virtual screening techniques ranging from simple fingerprint based similarity searching to the sophisticated docking algorithms reveals the inverse proportionality of the speed and accuracy of these algorithms, thus presenting a significant challenge, in enabling the use of computational tools to drug research. Some of the advantages and disadvantages of the structure-based (direct) and ligand-based (indirect) drug design techniques are typically discussed in terms of their requirements vis-a-vis the accuracy and time required for the analysis. The various integration strategies conceptualized to circumvent the above problems in the recent years are summarized with their merits and demerits.

We describe several computational methodologies used in aiding the chemical synthesis of drugs. We first summarize quantum mechanical approaches that weigh thermodynamical and kinetic factors in selecting the possible pathways during synthesis. The two major problems encountered in computational approaches are the efficient sampling of the conformational space and the incorporation of solvent effect into the system of interest. Thus, conformational search methodologies of small to medium sized molecules, with emphasis on cyclic molecules, are reviewed. Also, the analysis of the solvent effect on the synthesis of drug molecules and yield, using continuum methodologies as well as molecular dynamics, is discussed. How results from these studies are in turn fed back into detailed quantum mechanical calculations with supermolecules of solvent and reaction site are outlined. It is shown that the usage of several computational techniques hand-in-hand provides a plethora of information that may be utilized during the actual synthesis of drug molecules.